code: def test_linear(self, solver):
      jacobian_diag_part = np.float32([-0.5, -1.0])
      initial_state = np.float32([1.0, 2.0])
      fn = lambda: linear(solver, jacobian_diag_part, initial_state)
      fn = tf.function(fn, autograph=False, jit_compile=True)
      with tf.device(FLAGS.test_device):
          times, states = self.evaluate(fn())
      states_exact = (
          np.exp(
              jacobian_diag_part[np.newaxis, :] * times[:, np.newaxis]
          )
          * initial_state
      )
      self.assertAllClose(states, states_exact, rtol=1e-4)
  
file_path: probability/tensorflow_probability/python/math/ode/xla_test.py
imports: from absl import flags
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.ode import bdf
label_desc: Use image node_id 1 for calling the XLATest obj's underlying member method code with example usage: obj.test_linear(solver) without return types